1. Field of the Invention
The present invention relates to a measurement system and an information processing system using a nuclear magnetic resonance. More particularly, it relates to the measurement system and the image processing system that quantitatively evaluate neural fiber bundles being extracted based on diffusion tensor.
2. Description of the Related Art
In recent years, tractography has been developed, which represents a fiber bundle such as a white matter fiber, by utilizing a nuclear magnetic resonance imaging (hereinafter, referred to as “MRI”). This technique is now becoming established as a strong tool for a brain scientific research. In addition, this technique is expected to be applied to a diagnosis of lesion of the central nervous system, a preoperative examination of a brain surgical operation, and the like.
The tractography is based on a diffusion anisotropic measurement. In this measurement, MPGs (Motion Probing Gradient), being a gradient magnetic field that enhances a change of signal amount due to the molecular diffusion, is applied in at least seven directions so as to measure diffusion-weighted images, and diffusion tensor corresponding to each voxel of these diffusion-weighted images is calculated. In a fiber-like tissue such as a white matter made up of neural fibers, a direction in which the internal water molecules diffuse is restricted by the fiber, and this indicates anisotropy. Therefore, by using information of an eigenvalue and an eigenvector, which can be obtained by diagonalizing the diffusion tensor, a pixel having high diffusion anisotropy is sequentially traced along a direction in which a diffusion coefficient is maximized (a direction of the eigenvector having a maximum eigenvalue), thereby enabling an imaging of the fiber bundles. A technique for imaging the fiber bundles based on the diffusion tensor is described, for example, in the Japanese Unexamined Patent Application Publication No. 11000320, hereinafter referred to as “patent document 1”, and in “PROCEEDINGS OF INTERNATIONAL SOCIETY OF MAGNETIC RESONANCE IN MEDICINE, 320 (1999)”, hereinafter referred to as “non-patent document 1”.
The fiber bundles are traced as the following; voxels included in any area on the diffusion tensor image are set as origins, and fiber bundles passing through respective origins are traced, and a series of image data constituting each fiber bundle is stored. The area for the voxels being the origins is referred to as a seed area. In selecting an area of interest, an operator may specify any position in a magnetic resonance image, by way of example. Alternatively, an area having high diffusion anisotropy may be extracted based on the diffusion tensor, a brain area extracted from a result of a brain functional measurement such as fMRI (functional magnetic resonance image) may be used, or a specific portion obtained from priori information may be used.
In the brain functional measurement such as the fMRI, a brain activated area associated with a particular impulse is created as an image. In order to understand functions of the brain, it is important to know anatomical connectivity between these brain activated areas. There is a method being used frequently, which displays a three-dimensional image of neural fiber bundles between the brain activated areas being obtained by the brain functional measurement, and visually evaluates the connectivity of each neural path. In many cases, in order to figure out a positional relationship between the area of interest within the brain and each neural path, data of the neural fiber bundles is displayed in superimposing manner on an anatomical image such as a nuclear magnetic image.
One of the methods to quantitatively evaluate the connectivity is described in “MAGNETIC RESONANCE IN MEDICINE, 1077-1088 (2003)”, hereinafter, referred to as “non-patent document 2”. In drawing the fiber bundles, there exists uncertainty due to a noise, artifact, incomplete modeling of diffusion signals, and the like. In this method, the above uncertainty is represented in the form of local probability density function based on the diffusion model, and by using this probability density function, a probability of existence of fiber bundle connection between any two points is estimated.
However, in the conventional method that displays the neural fiber bundle data in superimposing manner on the anatomical image, it is not possible to quantitatively figure out the neural fiber bundles. In the method to estimate the probability of existence of fiber bundle connection between any two points, as global connectivity by using the probability density function, it is not possible to compare the connectivity intensity between any of the neural paths, with others.
The present invention has been made to solve the problems shown in the conventional techniques as described above, and an object of the present invention is to provide a measurement system and an image processing system in which fiber bundles passing through any VOI (volume of interest) are quantitatively figured out.